In this work we present an approach to extract the business logic of an application based on its generated logs. To do so we use process mining techniques to extract the model from the logs of an industrial application which are often large and hence difficult to analyze. We propose here a methodology to group the log according to similar elements, so that it can be presented to the user in separate fragments. We enrich this view of the model with semantic information based on the ontology we built.